资源环境科技发展态势分析平台

The current study aims at improving our common knowledge of precipitation and surface temperature variabilities in Iran across different time scales (from intra-annual to decadal) by using two methods (the cumulative spectral power and wavelet coherence analyses) and linking the variabilities to several teleconnection indices, namely Mediterranean Oscillation (MO), Quasi-biennial Oscillation (QBO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), and solar activity (~ Sunspot Number (SN)). Furthermore, the interdependence of the spectral components of indices is also explored. We divided the country to eleven climatic zones and performed the analysis for individual zones as well as for the total area by constructing the precipitation and temperature signals for the study period of 1979–2021 based on the gridded data. Based on the wavelet coherence analysis, the surface temperature and precipitation variations are strongly linked together, in particular at annual cycle and the phase status is predominantly anti-phase for all zones as well as for the all temporal scales. In addition, the MO can be regarded as a predictor of the annual variation of both variables over Iran as our results indicate a significant co-variability in the annual band between MO signal and these variables. Furthermore, a similar semi-annual component is detected in both MO and temperature signals with an anti-phase status, but the same component was not found in the precipitation. Other indices have also substantial influences on both temperature and precipitation, mostly at inter-annual and decadal periods. Based on the wavelet coherence and lagged correlation analyses, evidences of common periodicity, namely 11-year solar cycle, between SN and SOI signals is clearly revealed. Moreover, our results show that if the SN signal is considered as the cause and the SOI signal as the effect, the minimum value of the 11-year component of SOI occurs approximately 2.5 to 3 years after the maximum of the same component in the SN signal. By employing the cumulative spectral power analysis, the main quasi-periodic components of the climatic signals, the surface temperature, and precipitation with their power distribution are presented and compared in different frequency bands. The application of both methods on different zones over Iran is also addressed in addition to the whole area. The results show that although some indices have minor impact on the variabilities of the precipitation and temperature for the whole area in some frequency bands, but the large impact is found in a number of individual zones.